Customized Gesture Recognition for Educational Games

2016 ◽  
Vol 3 (2) ◽  
pp. 1
Author(s):  
Seong Jeong ◽  
HongJun Ju ◽  
Hyo-Rim Choi ◽  
TaeYong Kim
2022 ◽  
Vol 355 ◽  
pp. 03043
Author(s):  
Yushan Zhong ◽  
Yifan Jia ◽  
Liang Ma

In order to cultivate children’s imagination and creativity in the cognitive process, combined with the traditional hand shadow game, a children’s gesture education game based on AI gesture recognition technology is designed and developed. The game uses unity development platform, with children’s digital gesture recognition as the content, designs and implements the basic functions involved in the game, including AI gesture recognition function, character animation function, interface interaction function, AR photo taking function and question answering system function. The game is finally released on the mobile terminal. Players can recognize gestures through mobile cameras, interact with virtual cartoon characters in the game, watch cartoon character animation, understand popular science knowledge, and complete the answers in the game. The educational games can better assist children to learn digital gestures, enrich children’s ways of cognition, expand children’s imagination, and let children learn easily with happy educational games.


Author(s):  
Neo Wen Kye ◽  
Aida Mustapha ◽  
Noor Azah Samsudin

2013 ◽  
Vol 221 (2) ◽  
pp. 90-97 ◽  
Author(s):  
John L. Sherry

Millions in taxpayer and foundation euros and dollars have been spent building and testing educational video games, games for health, and serious games. What have been the fruits of this frenzy of activity? What educational video game has had the reach and impact of Sesame Street or Blues Clues television shows? By comparison, the Children’s Television Workshop (CTW) managed to get Sesame Street off the ground within a couple of years, writing the basic scientific literature on educational media design in the process. Not only is Sesame Street well known and proven, it laid the basis for every effective educational show to follow. This article explores the differences between the CTW scientific approach to educational media production and the mostly nonscientific approach consuming so many resources in the educational games, games for health, and serious games movements. Fundamental scientific questions that remain unanswered are outlined.


2020 ◽  
Vol 79 (1) ◽  
pp. 47-57
Author(s):  
O. G. Viunytskyi ◽  
A. V. Totsky ◽  
Karen O. Egiazarian

2020 ◽  
Vol 5 (2) ◽  
pp. 609
Author(s):  
Segun Aina ◽  
Kofoworola V. Sholesi ◽  
Aderonke R. Lawal ◽  
Samuel D. Okegbile ◽  
Adeniran I. Oluwaranti

This paper presents the application of Gaussian blur filters and Support Vector Machine (SVM) techniques for greeting recognition among the Yoruba tribe of Nigeria. Existing efforts have considered different recognition gestures. However, tribal greeting postures or gestures recognition for the Nigerian geographical space has not been studied before. Some cultural gestures are not correctly identified by people of the same tribe, not to mention other people from different tribes, thereby posing a challenge of misinterpretation of meaning. Also, some cultural gestures are unknown to most people outside a tribe, which could also hinder human interaction; hence there is a need to automate the recognition of Nigerian tribal greeting gestures. This work hence develops a Gaussian Blur – SVM based system capable of recognizing the Yoruba tribe greeting postures for men and women. Videos of individuals performing various greeting gestures were collected and processed into image frames. The images were resized and a Gaussian blur filter was used to remove noise from them. This research used a moment-based feature extraction algorithm to extract shape features that were passed as input to SVM. SVM is exploited and trained to perform the greeting gesture recognition task to recognize two Nigerian tribe greeting postures. To confirm the robustness of the system, 20%, 25% and 30% of the dataset acquired from the preprocessed images were used to test the system. A recognition rate of 94% could be achieved when SVM is used, as shown by the result which invariably proves that the proposed method is efficient.


2019 ◽  
Vol 8 (2) ◽  
pp. 157
Author(s):  
Enceng - Yana ◽  
Acep - Komara ◽  
Aan - Anisah

<p><strong>ABSTRAK</strong></p><p>Penelitian ini bertujuan untuk mengembangkan media pembelajaran akuntansi berbantuan <em>game</em> edukatif berbasis <em>android</em>, sehingga dihasilkan media pembelajaran akuntansi berupa <em>game</em> edukatif  yang  valid, praktis dan efektif. Model yang digunakan dalam penelitian  pengembangan ini adalah ADDIE<em>.</em> Teknik Pengumpulan data yang digunakan adalah angket dalam hal ini berupa lembar validasi, angket respons mahasiswa, test dan studi dokumentasi. Adapun teknik analisa data yang digunakan adalah teknik deskriptif persentase. Hasil penelitian ini menunjukan media pembelajaran <em>game </em>eduktif yang dikembangkan valid, praktis dan efektif sesuai dengan tujuan penelitian serta mampu meningkatkan kemampuan <em>analysis ability </em>mahasiswa khususnya pada pokok materi rekonsiliasi bank.</p><p><em><strong>ABSTRACT</strong></em></p><p><em>This research aims to develop accounting learning media assisted with android-based educational games, therefore, valid, practical and effective accounting learning media produced. The model used in this research development is ADDIE, while the techniques of data collection used are questionnaires in the form validation sheets, students' response sheets, tests, and documentation study. The technique of data analysis used is a descriptive percentage by changing the quantitative data to become percentage form. The results of this study indicate that the development of educational learning media is valid, practical, and effective, it is in accordance of the study and can improve students' skill in analyzing the ability especially on bank reconciliation subject.</em></p>


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